Redo-TAVI with the ACURATE neo2 and Prime XL for balloon-expandable transcatheter heart valve failure
Bibliographic record
Abstract
BACKGROUND: There are limited data regarding treatment for failed balloon-expandable transcatheter heart valves (THVs) in redo-transcatheter aortic valve implantation (TAVI). AIMS: We aimed to assess THV performance, neoskirt height and expansion when performing redo-TAVI with the ACURATE platform inside a SAPIEN 3 (S3) compared to redo-TAVI with an S3 in an S3. METHODS: Redo-TAVI was performed on the bench using each available size of the S3, the ACURATE neo2 (ACn2) and the next-generation ACURATE Prime XL (AC XL) implanted at 2 different depths within 20 mm/23 mm/26 mm/29 mm S3s serving as the "failed" index THV. Hydrodynamic testing was performed to assess THV function. Multimodality assessment was performed using photography, X-ray, microcomputed tomography (micro-CT), and high-speed videos. RESULTS: The ACURATE in S3 combinations had favourable hydrodynamic performance compared to the S3 in S3 for all size combinations. In the 20 mm S3, redo-TAVI with the ACn2 had lower gradients compared to the S3 (mean gradient 16.3 mmHg for the ACn2 vs 24.7 mmHg for the 20 mm S3 in 20 mm S3). Pinwheeling was less marked for the ACURATE THVs than for the S3s. On micro-CT, the S3s used for redo-TAVI were underexpanded across all sizes. This was also observed for the ACURATE platform, but to a lesser extent. CONCLUSIONS: Redo-TAVI with an ACn2/AC XL within an S3 has favourable hydrodynamic performance and less pinwheeling compared to an S3 in S3. This comes at the price of a taller neoskirt.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".